Abstract
Exploring predictors of premature coronary artery disease (PCAD) based on a real-world study. We employed 50,190 individuals and collected their baseline characteristics, including medical history, anthropometric measurements, and blood biochemistry indicators from 2001 to 2018. PCAD were screened strictly based on diagnostic and exclusion criteria, and ultimately 14,469 individuals (including 387 in coronary angiography for the diagnosis of PCAD and 14082 in the control who thought that the degree of coronary stenosis did not meet diagnostic criteria) were included in analyzed. Propensity score matching (PSM) was used to assess these patients. We used multivariable Cox proportional hazards regression to identify risk factors and developed a nomogram to estimate the risk of major adverse cardiac events (MACE) over the 36-month follow-up period. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of the risk factors. All patients were followed up for 36 months，and a survival curve was plotted. Before PSM matching, PCAD patients exhibited significantly higher levels of several risk factors, including body mass index (BMI), waist circumference (WC), triglycerides (TG), hemoglobin A1c (HbA1c), glucose, and various cardiovascular indicators such as systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP), compared to the control group (P < 0.001). After PSM matching, only the body roundness index (BRI) remained significantly higher in PCAD patients (P < 0.001).In Cox regression analysis and nomogram development, gender, age, smoking, serum creatinine, aspartate aminotransferase (AST), ABSI, and BRI were identified as significant risk factors for PCAD (P < 0.01-0.05), both before and after PSM matching. The ROC curve analysis showed that combining ABSI and BRI improved diagnostic performance, with an area under the curve (AUC) of 0.73.Survival analysis revealed that high ABSI and BRI significantly predicted poorer prognosis in PCAD patients, regardless of PSM matching (P < 0.05). Further survival analysis combining ABSI and BRI demonstrated that, after PSM matching, high ABSI consistently indicated a worse prognosis, irrespective of BRI levels. ABSI and BRI are high-risk factors for PCAD, and ABSI combined with BRI with a higher diagnosis. High ABSI is associated with poor prognosis in PCAD patients, and the exact mechanism needs to be further explored.